|
CSL865: Special Topics in Computer Applications: Machine Learning
General Information
Instructor: Parag Singla (email: parags AT cse.iitd.ac.in)
Class Timings (Slot F):
- Tuesday, 11:00am - 11:55am
- Thursday, 11:00am - 11:55am
- Friday, 11:00am - 11:55am
Venue:IV LT 2
Teaching Assistant: Yamuna Prasad (email: csz098192 AT cse.iitd.ac.in)
Announcements
- [Wed Oct 31]: Assignment 3 is out! Due Date: Friday Nov 16 (in class).
- [Thu Oct 11]: No Class on Friday Oct 12. Extra class on Monday Oct 15. 2pm - 3pm. Venue: Bharti 201.
- [Sun Sep 30]: Extra class on Monday Oct 1. 2pm - 3pm. Venue: Bharti 204.
- [Sat Sep 22]: Assignment 2 is out! Due Date: Tuesday October 16 (in class)
- [Tue Sep 11]: Assignment 1 is now due on Friday September 14 (in class).
- [Wed Aug 20]: Assignment 1 is out! Due Date: Tuesday September 11 (in class).
- [Wed Aug 7]: After all the confusion, we seem to have settled for IV LT 2 as our
permanent venue for the class.
-
[Mon Aug 6]: Permanent venue for the class will be Block III, Room 356.
- [Mon Jul 30]: Venue for tomorrow's (Tue Jul 31) class
is IV LT 2.
- [Thu Jul 26]: On Fri July 27, we will plan
on meeting for additional half an hour after the regular slot i.e. the class time would be
11:00 am - 12:30 pm.
Course Content
Week | Topic | Book Chapters | Supplementary Notes |
1 | Introduction | Duda, Chapter 1 | |
2,3 | Linear and Logistic Regression, Gaussian Discrimnant Analysis | Bishop, Chapter 3.1, 4 |
lin-log-reg.pdf, gda.pdf |
4,5 | Support Vector Machines | Bishop, Chapter 7.1 | svm.pdf |
6 | Neural Networks | Mitchell, Chapter 4 |
nnets.pdf |
7 | Decision Trees | Mitchell, Chapter 3 |
dtrees.pdf |
8,9 | Naive Bayes, Bayes Classifier, Bayesian Networks, Markov Networks |
Mitchell, Chapter 6 |
nb.pdf,
bayes.pdf
Conjugate Prior
mn.pdf |
10,11 | Learning Theory, Model Selection | Mitchell, Chapter 7 |
theory.pdf
model.pdf |
12 | K-Means, Gaussian Mixture Models, EM | |
kmeans.pdf
gmm.pdf
em.pdf |
13 | PCA and ICA | |
pca.pdf
ica.pdf |
14 | Revision | | |
Review Material
References
- Pattern Recognition and Machine Learning. Christopher Bishop. First Edition, Springer, 2006.
- Pattern Classification. Richard Duda, Peter Hart and David Stock. Second Edition, Wiley-Interscience, 2000.
- Machine Learning. Tom Mitchell. First Edition, McGraw-Hill, 1997.
Assignment Submission Instrutions
- You are free to discuss the problems with other students in the class. You should include the names of
the people you had discussion with in your submission.
- All your solutions should be produced independently without refering to any discussion notes.
- All the non-programming solutions should be submitted using a hard copy. If you are writing
by hand, write legibly.
- All the programming should be done in MATLAB.
Include comments for readability.
- Required code should be submitted using Moodle Page.
- You should archive all your submission (code) in one single zip file. This zip file
should be named as "yourentrynumber_firstname_lastname.zip". For example, if your entry number is
"2008anz7535" and your name is "Nilesh Pathak", your submission should be named as
"2008anz7535_nilesh_pathak.zip
- Honor Code: Any cases of copying will be awarded a zero on the assginment. More severe penalties may follow.
- Late Policy: You will lose 20% for each late day in submission. Maximum of 2 days late submissions are allowed.
Assignments
- Assignment 3. Due Date: Friday November 16 (in class). Coding problem due on Saturday Nov 24.
- Assignment 2. Due Date: Tuesday October 16 (in class).
- Assignment 1. Due Date:
Tuesday September 11 (in class). Friday September 14 (in class).
Datasets
Grading Policy
Assignments (3) | 24% |
Class Participation | 6% |
Minor I | 15% |
Minor II | 15% |
Major | 40% |
|